1. Field of the Invention
The present invention relates to a face detection method and a face detection device for detecting face images contained in digital images, as well as a program therefor.
2. Description of the Related Art
Conventionally, particularly in the fields of image correction, security system, and digital camera control, face detection methods for detecting faces contained in digital images have been studied and various face detection methods have been proposed. One of such methods is a face detection method in which a digital image is scanned using a sub-window and whether or not an image within the sub-window is a face image containing a face is sequentially determined using classifiers, to detect a face contained in the digital image (see, for example, “Fast Omni-Directional Face Detection”, Shihong LAO et al., Meeting on image recognition and understanding (MIRU2004) pp. II271-II276, 2004, and U.S. Patent Application Publication No. 20020102024).
The face images includes frontal face images that mainly contain frontal faces with front orientation and side face images that mainly contain side faces with side orientation. The frontal face images and the side face images have different image features from each other. Therefore, in order to detect both of the frontal face images and the side face images from images subjected to detection, typically, separate classifiers are used for discriminating the frontal face images and discriminating the side face images. For example, the classifier for discriminating the frontal face images learns features of frontal faces using different sample images representing frontal faces, and the classifier for discriminating the side face images learns features of side faces using different sample images representing side faces.
However, in the above-described face detection method using the classifiers, if a non-face pattern, which has features similar to the features of a face, is present in an image to be detected, the non-face image may falsely be detected as being a face image. Particularly, since the side face is formed by smaller number of face parts than those forming the frontal face and has a smaller face area than that of the frontal face, quantities of features of the side face appearing in an image is small. In addition, the side face has a complicated contour. Further, it is necessary to detect both of left- and right-side faces. Therefore, false detection rates for the side face images tend to be higher than false detection rates for the frontal face images.
As described above, when faces contained in images are detected based on features of the faces in the images, there is at least a possibility of false detections, and therefore, it is desired to detect faces while minimizing a false detection rate. Further, since the false detection rate typically varies depending on the orientation of the face, it is desired to reduce the false detection rate for the orientations of faces that tend to result in high false detection rates.